| Citation: |
FU Hao, CUI Peiqiang, TANG Xi, GAN Shuang, WAN Tianyi, ZHANG Zewu, WU Fan, ZHANG Liqi. Source-load Matching and Capacity Configuration Optimization for Wind and Solar Energy Storage System in Expressways[J]. Journal of South China Normal University (Natural Science Edition), 2024, 56(2): 32-41. DOI: 10.6054/j.jscnun.2024020
|
An electric vehicle (EV) charging load prediction model was established to predict the time distribution characteristics of EV charging load by Monte Carlo simulation, a source-load matching optimization strategy was proposed considering the parameters of charging piles and charging/swapping modes, and a comprehensive evaluation system for wind and solar energy storage system was established. Using improved genetic algorithms for planning and solving to obtain the optimal capacity configuration. Taking a service area in Shandong Province as an example, the results show that the EV charging load prediction curve presents a "bimodal" pattern during the day. The number of charging piles and the maximum charging power in the service area are reasonably set, and the charging/swapping mode with battery swapping participation is selected to make the load energy consumption curve close to the photovoltaic power generation curve. Compared with the initial scheme, the improved genetic algorithm can improve the closeness of the optimal scheme, and can realize the charging of energy storage system and the connection of residual power.
| [1] |
张良, 孙成龙, 蔡国伟, 等. 基于PSO算法的电动汽车有序充放电两阶段优化策略[J]. 中国电机工程学报, 2022, 42(5): 1837-1852. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDC202205017.htm
ZHANG L, SUN C L, CAI G W, et al. Two-stage optimization strategy for coordinated charging and discharging of EVs based on PSO algorith[J]. Proceedings of the CSEE, 2022, 42(5): 1837-1852. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDC202205017.htm
|
| [2] |
LI X H, WANG Z P, ZHANG L, et al. Electric vehicle behavior modeling and applications in vehicle-grid integration: an overview[J]. Energy, 2023, 268: 126647/1-16.
|
| [3] |
HAO Y, DONG L, LIANG J, et al. Power forecasting-based coordination dispatch of PV power generation and electric vehicles charging in microgrid[J]. Renewable Energy, 2020, 155: 1191-1210. doi: 10.1016/j.renene.2020.03.169
|
| [4] |
LI Q T, WANG J X, ZHANG Y, et al. Multi-period generation expansion planning for sustainable power systems to maximize the utilization of renewable energy sources[J]. Sustainability, 2020, 12(3): 2630-2639.
|
| [5] |
FAN M, SUN K, LANE D, et al. A novel generation rescheduling algorithm to improve power system reliability with high renewable energy penetration[J]. IEEE Transactions on Power Systems, 2018, 33(3): 3349-3357. doi: 10.1109/TPWRS.2018.2810642
|
| [6] |
刘俊磊, 刘新苗, 卢洵, 等. 高比例新能源系统供需平衡分析方法和对策[J]. 高电压技术, 2023, 49(7): 2711-2724. https://www.cnki.com.cn/Article/CJFDTOTAL-GDYJ202307003.htm
LIU J L, LIU X M, LU X, et al. Analysis methods and countermeasures of supply and demand balance of high proportion of new energy system[J]. High Voltage Engineering, 2023, 49(7): 2711-2724. https://www.cnki.com.cn/Article/CJFDTOTAL-GDYJ202307003.htm
|
| [7] |
张歆蒴, 陈仕军, 曾宏, 等. 基于源荷匹配的异质能源互补发电调度[J]. 电网技术, 2020, 44(9): 3314-3320. https://www.cnki.com.cn/Article/CJFDTOTAL-DWJS202009015.htm
ZHANG X S, CHEN S J, ZENG H, et al. Heterogeneous energy complementary power generation dispatching based on output-load matching[J]. Power System Technology, 2020, 44(9): 3314-3320. https://www.cnki.com.cn/Article/CJFDTOTAL-DWJS202009015.htm
|
| [8] |
张程, 匡宇, 邹复民, 等. 考虑风光不确定性与电动汽车的综合能源系统低碳经济调度[J]. 电力自动化设备, 2022, 42(10): 236-244. https://www.cnki.com.cn/Article/CJFDTOTAL-DLZS202210030.htm
ZHANG C, KUANG Y, LIU F M, et al. Low carbon economic dispatch of integrated energy system considering wind and solar uncertainty and electric vehicles[J]. Electric Power Automation Equipment, 2022, 42(10): 236-244. https://www.cnki.com.cn/Article/CJFDTOTAL-DLZS202210030.htm
|
| [9] |
张智刚, 康重庆. 碳中和目标下构建新型电力系统的挑战与展望[J]. 中国电机工程学报, 2022, 42(8): 2806-2819. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDC202208002.htm
ZHANG Z G, KANG C Q. Challenges and prospects for constructing the new-type power system towards a carbon neutrality future[J]. Proceedings of the CSEE, 2022, 42(8): 2806-2819. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDC202208002.htm
|
| [10] |
JAVED M S, MA T. Techno-economic assessment of a hybrid solar-wind-battery system with genetic algorithm[J]. Energy Procedia, 2019, 158: 6384-6392. doi: 10.1016/j.egypro.2019.01.211
|
| [11] |
MEINRENKEN C J, MEHMANI A. Concurrent optimization of thermal and electric storage in commercial buildings to reduce operating cost and demand peaks under time-of-use tariffs[J]. Applied Energy, 2019, 254: 113630/1-13.
|
| [12] |
LIU Z Q, CUI Y P, WANG J Q, et al. Multi-objective optimization of multi-energy complementary integrated energy systems considering load prediction and renewable energy production uncertainties[J]. Energy, 2022, 254: 1-16.
|
| [13] |
夏延清. 基于时空大数据技术的高速公路出行特征分析[D]. 北京: 北方工业大学, 2020.
XIA Y Q. Analysis of highway travel characteristics based on spatio-temporal big data[D]. Beijing: North China University of Technology, 2020.
|
| [14] |
HE Z Y, CHENG Y, HU Z H, et al. Multi-time simulation of electric taxicabs' charging demand based on residents' travel characteristics[C]. 2017 IEEE Conference on Energy Internet and Energy System Intergration. Piscataway: IEEE.
|
| [15] |
高淑萍, 李晓芳, 宋国兵, 等. 基于Pearson相关系数与广义S变换的低压直流微电网的故障选线方法[J]. 电力系统保护与控制, 2023, 51(15): 120-129. https://www.cnki.com.cn/Article/CJFDTOTAL-JDQW202315012.htm
GAO S P, LI X F, SONG G B, et al. Fault line selection method of a low-voltage DC microgrid based on the Pearson correlation coefficient generalized S-transform[J]. Power System Protection and Control, 2023, 51(15): 120-129. https://www.cnki.com.cn/Article/CJFDTOTAL-JDQW202315012.htm
|
Supported by: Beijing Renhe Information Technology Co., Ltd. 
DownLoad: